Rasa is an open source machine learning framework for developers to build contextual AI assistants. It offers a set of tools that allow developers to create conversational AI, including natural language understanding, dialogue management, and automated machine learning. With Rasa, developers can easily create assistants that are able to understand complex user interactions, carry conversations over multiple turns, and respond to user requests in natural language. Rasa also provides an array of integrations that let developers easily deploy their AI assistants to popular messaging platforms such as Slack, Messenger, and Telegram.

OpenNMT is an open-source neural machine translation (NMT) toolkit developed by Harvard NLP researchers. OpenNMT is designed to be simple, fast and extensible, allowing researchers to quickly prototype their ideas and then scale to production systems. The toolkit supports both encoder-decoder and transformer architectures and provides a wide range of features such as multi-GPU training, beam search, and support for multiple languages. OpenNMT also provides a library of pre-trained models and tutorials to help users get started quickly and easily. OpenNMT is free and open-source software, available for anyone to use and modify.

Gensim is an open-source library for unsupervised topic modelling and natural language processing. It allows developers to quickly and efficiently train models for a variety of tasks, including document vectorization, topic modelling, classification, similarity detection and more. Gensim utilizes efficient algorithms, such as Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA) and Random Projections (RP), to process large amounts of text data quickly and accurately. It also provides an easy-to-use API with a variety of tools to help developers quickly and easily build their own models. Gensim is designed to be both simple to use and powerful enough to handle complex tasks. Facebook page URL: Not applicable.

Natural Language Toolkit (NLTK) is an open-source library of tools for natural language processing (NLP). It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. NLTK is accompanied by extensive documentation and tutorials which make it accessible to both novice and expert users. NLTK is the most popular Python library for natural language processing, and is used by researchers, educators, students, and industry practitioners.

Stanford CoreNLP is a suite of tools for natural language processing, including tokenization, part of speech tagging, named entity recognition, sentiment analysis, and coreference resolution. It is built on the Java platform and runs on most platforms. CoreNLP is open source, and features an intuitive user-friendly interface and easy to use APIs. CoreNLP is designed to be efficient and allow users to quickly develop and deploy natural language processing applications. CoreNLP is also designed to be highly extensible, so users can add new features and customize existing features. CoreNLP also has an active community of developers who are constantly improving and developing new features.

SpaCy is an open-source library for industrial-strength natural language processing in Python and Cython. It features state-of-the-art speed and accuracy for deep learning-based models in NLP, and is designed to help you build applications that process and “understand” large volumes of text. It supports over 50 languages and is widely used in production for tasks such as text classification, information extraction, question answering, and more. It is a library for advanced Natural Language Processing that is designed to be both fast and easy to use. With its versatile selection of pre-trained models and its API, it provides powerful tools for developers and researchers to build applications that use natural language processing. SpaCy is a project of Explosion AI, a software start-up based in Berlin.

AllenNLP is an open-source NLP research library built on PyTorch. It provides a platform for researchers to develop state-of-the-art models in natural language processing and other areas of AI. The library is designed to make it easy to develop models and experiments quickly with minimal code. It also provides helpful tools to facilitate model development, such as a web-based demo server, a model zoo, and tutorials. AllenNLP has been used in a variety of research projects, ranging from question answering to machine translation.

Huggingface Transformers is an open-source library for state-of-the-art natural language processing (NLP). It provides a unified interface for using most of the current best-in-class pretrained models for a variety of tasks including text classification, question answering, text generation, and many more. The library also supports fine-tuning and customizing pretrained models to suit the particular needs of a user, allowing for greater control and accuracy in the results. Huggingface Transformers is compatible with both TensorFlow and PyTorch, making it easy to use in any type of project. With an extensive set of features, users can quickly and easily build powerful NLP applications.

BERT (Bidirectional Encoder Representations from Transformers) is an open source natural language processing (NLP) system developed by Google Research. It is a deep learning model that uses unsupervised techniques to pre-train contextual representations from unlabeled text. BERT is designed to help computers understand the meaning of ambiguous language in text by using surrounding text to determine the most relevant meaning. It can be used for a variety of tasks such as question answering, sentiment analysis, text classification, and more. BERT has achieved state-of-the-art results in many NLP tasks and has been adopted by hundreds of companies and organizations.

An AI-powered tool that can transform any image into a work of art using style transfer techniques. With support for multiple artistic styles and easy customization, this app is a fun and creative way to explore the possibilities of computer vision.